Package: rocc 1.3

rocc: ROC Based Classification

Functions for a classification method based on receiver operating characteristics (ROC). Briefly, features are selected according to their ranked AUC value in the training set. The selected features are merged by the mean value to form a meta-gene. The samples are ranked by their meta-gene value and the meta-gene threshold that has the highest accuracy in splitting the training samples is determined. A new sample is classified by its meta-gene value relative to the threshold. In the first place, the package is aimed at two class problems in gene expression data, but might also apply to other problems.

Authors:Martin Lauss

rocc_1.3.tar.gz
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rocc.pdf |rocc.html
rocc/json (API)

# Install 'rocc' in R:
install.packages('rocc', repos = c('https://lau-mel.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.56 score 36 scripts 162 downloads 1 mentions 3 exports 6 dependencies

Last updated 5 years agofrom:3899923018. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 31 2024
R-4.5-winOKOct 31 2024
R-4.5-linuxOKOct 31 2024
R-4.4-winOKOct 31 2024
R-4.4-macOKOct 31 2024
R-4.3-winOKOct 31 2024
R-4.3-macOKOct 31 2024

Exports:o.roccp.rocctr.rocc

Dependencies:bitopscaToolsgplotsgtoolsKernSmoothROCR